Drought Prediction with PDSI, Lars-WG5 and HadCM3 (Case Study Neyshabour Basin)

According to the increasing of population and human needs to food in one hand، and emerging of severe drought and its consequences in the other hand، has led to consideration of this creeping phenomenon prediction in different societies. In this research، predicting the influential climatic parameters on drought occurrence like monthly precipitation، minimum and maximum temperature was particularly done with HadCM3 large scale model. Also، the application of the large scale model outputs and transforming them in to the applicable data for regional drought prediction accomplished with LARS-WG5 downscaling model، in Neyshaboor Plain. Moreover، the palmer drought Monitoring Model based on palmer index (PDSI) applied. Data processing and climatic data prediction were satisfied with two statistical periods of 1991-2010 as observation period and 2011-2040 as prediction period. Also، according to the models output for Neyshaboor station in 20-years observation period، predictions showed that precipitation will increase in Neyshaboor station in the future 30-years period. On the whole، the climatic models result showed that will increase in future. The minimum temperature of climatic models outputs indicated that in the first decade relation to the base period 6% increasing overall، the second decade like the first one، and in the third decade yielded 4% increasing. The climatic models output for maximum temperature presented increasing trend in prediction period relation to the base period. This result indicated 1% increasing in all three decades for maximum temperature. The drought monitoring model output in Neyshabour station showed that medium، severe and very severe drought classes will decrease in future three decades in relation to the 20-year observation period. For decennial comparisons we found that the extreme drought in the first decade from 120 month only has five month in this decade، and other two decade less than first decade.